The purpose of this research is to gain a better understand of adaptation of elderly living in a retirements community as they approach old-old age and face increasing frailty. The proposed study seeks an indepth understanding of personal (psychological and economic), environmental and social resources and services needs of old-old residents of a Florida retirement community. It aims to test a conceptual model for predicting continued psychosocial well-being and independent living of old- old who experience health problems. In the framework of this model, the buffering roles of diverse personal, environmental and social resources are explored in diminishing the adverse effects of ill health in late life. The model will be tested as it predicts components of psychosocial well-being and of outcomes of residential relocation to more sheltered settings. A three-wave longitudinal design is proposed with follow-ups at one year intervals and a fourth year status check. The sample will be comprised of 800 old-old (age 75+) residents of a large Florida retirement community. Only respondents who are in good functional health and free of major mental impairments will be included in the longitudinal study. Personal interviews will obtain data during an initial interview and two follow-up interviews. Telephone interviews will be conducted with respondents who relocated outside Florida, with all respondents at the fourth year status check and with families of those respondents who have become uninterviewable or who have died in the course of the study. The study will provide detailed information on respondent's social support networks, documenting the types of resources exchanged, the directionality of exchanges and satisfaction with the relationships for both formal and informal supports. Data analyzes will also provide a description of the stability of personal, environmental and social resources and of outcomes. They will also yield information about the role of diverse resources in buffering the impact of illness on psychosocial outcomes and on residential stability. A carefully designed measurement model, coupled without longitudinal designed, provides the basis for testing our causal model. Data analysis will utilize multivariate and structural equations with multiple indicator models to assess lagged, instantaneous and reciprocal effects of our causal model. Event history analysis will be conducted to examine predictors of discrete events.